Eleventh IEEE International Workshop on Smart Service Systems
SmartSys 2026

June 22, 2026 | Messina, Italy

http://smartsys2026.dii.unipi.it

Co-located with the IEEE International Conference on Smart Computing (IEEE SMARTCOMP 2026)

Download CFP in PDF version here

Technology succeeds when it provides benefits to the society either directly or indirectly. Understanding the societal and economic impact and human-centered aspects of a smart system or technology in advance and designing the system a-priori with potential value-added services help spur the discoveries of new tools, methodologies and innovative services. Smart service systems span across a variety of socio-technical facets comprising of devices, people, organizations, environments and technologies to sense, actuate, control and assess the physical, cyber and societal artifacts of the human service systems. Besides the systems being self-adaptive and fault-tolerant, need to be designed in such a way that it can continuously increase the quality and productivity, the compliance and sustainability of the smart services it offers. While human-centered perspective and cognitive learning help create multi-facet value added services and catalyze the sustained economic growth of smart service systems, understanding the multi-modal sensing, control, heterogeneity and interdependency between different physical, virtual and logical components of such a complex system will enable the realization of new transformative smarter service systems. If successful, this can help improve the quality-of-experience of the customers, quality-of-life of the citizens and quality-of returns of the stakeholders and investors.

Nurturing the development of smart service systems seeks for inter- and trans-disciplinary crosscutting research threads from system and operational engineering, computer science and information systems, social and behavioral science, computational modeling and industrial engineering etc. The goal of this workshop is to bring together practitioners and researchers from both academia and industry in order to have a forum for discussion and technical presentations on the fundamental knowledge and principles of smart service systems that enable the value co-creation in sensing, actuating, data analytics, learning, cognition, and control of human centric cyber-physical-social systems and future of work.

Topics of interest include, but are not limited to:

• Innovative tools, methodologies and solutions for smart service systems; examples include personalized healthcare, smart energy, smart cities, smart manufacturing, intelligent transportation, education, precision medicine and agriculture, national security etc.
• Information extraction and interpretation from sensors, actuators, smart phones, wearable devices (e.g., smart watches), and humans
• Context and situational awareness of smart service systems
• Design of people-centric services and technologies for providing better services such as food, transportation and places to live
• Novel architectures and interoperable solutions for Internet of Things
• Models and methodologies for designing systems of systems
• Big data analytics approaches for providing better customer services, and innovating new types of sustainable services
• Edge AI and federated learning approaches enabling real-time, privacy-preserving intelligence in distributed smart service systems.
• Modeling, analysis, co-production, and co-evolution of human activity, behavior and interaction for the effective adaptation and percolation of longitudinal smart service systems
• Role of machine learning, artificial intelligence, robotics, pervasive computing, blockchain, control theory, information and communications technologies
• Role of formal methods in computer networks, cyber-physical systems, Internet-of-Things and machine learning
• Design and developments of intelligent systems, intelligent enterprises and cyber-physical-social-systems
• Design of inter-dependent complex global systems such as healthcare, smart grid, computer networks, logistics and supply-chains, financial markets etc.
• Smart infrastructure and testbed to support the integration of autonomous systems and innovative applications
• Digital twins for modeling, monitoring, and optimizing human-centric cyber-physical-social smart services.
• Design and implementation of analytical methods, simulation software and experimental testbeds to evaluate the key performance indicators of smart services
• Design of approaches for trustworthiness of human-centered smart systems and algorithms
• Design and implementation of persuasive smart systems and smart systems for behavior change support
• Fairness and Bias Mitigation in AI algorithms for pervasive systems
• Fair, explainable, interpretable, trustworthy, and private, AI systems with social/societal impact in areas of interest.
• Leveraging Human-in-the-Loop Feedback for Enhanced Context-Awareness in pervasive systems

SmartSys 2026 Program

Keynote

Talk Title: Enabling Physical AI for Resilient Community Infrastructure

Speaker: Prof. Nalini Venkatasubramanian, Dept. of Computer Science, University of California, Irvine, USA

Talk Abstract: Recent advances in cyberphysical systems, Internet-of-Things, pervasive computing, and AI technologies have enabled the creation of a new wave of smart infrastructure for communities. In this talk, I outline a principled methodology and a set of techniques to support the observation, analysis, and adaptation of community infrastructure systems through physical AI: an approach that integrates physics-based models with data-driven methods. I will highlight our experiences with creating AI-enabled infrastructures in multiple contexts - from smart safe buildings to community-scale smart water and power infrastructures that are resilient to urban growth and extreme events. In routine operation, these systems can benefit from continuous monitoring and analytics to optimize costs and enable early detection of localized failures and anomalies. During extreme events, the same cyber-physical platform must scale to estimate the state of regional infrastructure and assess impacts on populations and essential services. Achieving resilience for community-scale infrastructures requires coordinated integration across system layers, including devices, networks, data processing, analytics, and user interaction. We present middleware techniques for physical AI systems that enable intelligent multimodal data acquisition from diverse sources, selective exchange of data and insights over heterogeneous networks, and extraction of higher-level semantic observations to support real-time decision-making. Finally, we argue that safely composing these techniques, while navigating inherent trade-offs, will require neurosymbolic approaches capable of reasoning about infrastructure behavior. Such approaches are essential to building robust, adaptive lifelines for the resilient communities of the future.

Speaker Biography: Nalini Venkatasubramanian is a Professor in the School of Information and Computer Science and Co-Director for the Center for Emergency Response Technologies at the University of California, Irvine. She has extensive research and industry experience in distributed systems, adaptive middleware, pervasive and mobile computing, cyberphysical systems, distributed multimedia, and formal methods, with over 350 publications in these areas. She is the recipient of the NSF Career Award, multiple Teaching Excellence Awards, several best paper awards, a Test-of-Time Award by the IEEE CNOM committee, and was named as one of the Stars in Networking by the CRA. Prof. Venkatasubramanian has served in advisory committees for governmental agencies for smart and safe communities, steering and organizing committees of conferences on middleware, distributed computing, and cyberphysical systems, and on the editorial boards of journals. She received her Ph.D. in Computer Science from the University of Illinois in Urbana-Champaign. Before arriving at UC Irvine, Nalini was a Research Staff Member at the Hewlett-Packard Laboratories in Palo Alto, California. Prof. Venkatasubramanian is an IEEE Fellow, AAAS Fellow, Fellow of the AAIS, an ACM Distinguished Engineer, and an IEEE Distinguished Contributor.

Submission instructions

Authors are invited to submit regular (full) papers for presentation at the workshop, describing original, previously unpublished work, which is not currently under review by another workshop, conference, or journal. Regular papers should present novel perspectives within the general scope of the workshop.

Each accepted paper will require a full SMARTCOMP registration (no registration is available for workshops only).

Important dates

Manuscript submission: March 23, 2026 (extended, firm)

Paper acceptance notification: April 29, 2026

Camera-ready paper submission: May 20, 2026

Workshop date: June 22, 2026

Organizing Committees

Workshop Co-Chairs:

• Nirmalya Roy, University of Maryland, Baltimore County, USA
• Carlo Vallati, University of Pisa, Italy
• Gurdip Singh, George Mason University, USA

Technical Program Co-Chairs:

• Mohamed Nafea, Missouri University of Science & Technology, USA
• Marco Pettorali, University of Pisa, Italy

Publicity Chairs:

• Jacopo Sabatino, University of Florence, Italy
• Avijoy Chakma, Bowie State University, USA

Technical Program Committee:

• Alberto Gotta, ISTI-CNR & CNIT, Italy
• Amna Mazen, Michigan Technological University, USA
• Antonio Virdis, University of Pisa, Italy
• Armir Bujari, University of Bologna, Italy
• Aryya Gangopadhyay, University of Maryland Baltimore County (UMBC), USA
• Carlo Puliafito, University of Pisa, Italy
• Enrico Casella, Pennsylvania State University, USA
• Fabrizio De Vita, University of Messina, Italy
• Francesca Righetti, Pegaso University, Italy
• Francesco Longo, University of Messina, Italy
• Giovanni Merlino, University of Messina & National Interuniversity Consortium for Informatics (CINI), Italy
• Jian Liu, Missouri University of Science and Technology & Nanjing University of Information Science and Technology, USA
• Jianhui Yue, Michigan Technological University, USA
• Marco Morana, University of Palermo, Italy
• Marco Tiloca, RISE Research Institutes of Sweden, Sweden
• Xinyue Zhang, Kennesaw State University, USA